Zirconia Toughened Alumina Femoral Head and Acetabular Socket: Process optimization, Designing, Fabrication and Properties

Despite several decades of research for new materials for articulating joints in orthopedic applications, the efforts to develop patient-specific prototype of such biomaterial devices are rather limited. While addressing this aspect, the present work demonstrates an integrated manufacturing approach how to fabricate zirconia toughened alumina femoral head and acetabular socket initiation with composition and process optimization, and designing of prototypes. The properties and performance of a such ceramic components significantly depend on the microstructue (grain size) and sinter density, it is therefore important to optimize both the process parameters (sintering temperature, sintering time) and material parameters (sinter–aid addition and reinforcement content) to obtain tough and strong materials. Based on considering the fundamental densification-grain size relationship and using the predictive linear, quadratic or interactive response among the process and material parameters, the adopted response surface methodology (RSM) approach is shown to provide excellent capability to predict sinter density and grain size with significant statistical correlation between experimental and predicted values. Summarising, the optimization study establishes that sintering of 5 wt.% zirconia toughened alumina sintered with 800 ppm MgO sinter-aid at 1600oC for 6h can exhibit a great combination of relative density, compressive strength (1100 MPa), tensile strength (200 MPa) and SEVNB fracture toughness (4.3 MP m1/2). In order to assess the cytocompatibility properties, C2C12 mouse myoblast cells were grown on the ZTA composite having the best combination of mechanical properties. The results of MTT assay reveal an increase in the number of mitochondrially active cells with time in culture for a period of up to 3 days. The fluorescence microscopic observations also confirmed good cell attachment and cell-to-cell contact with cellular bridge formation. In view of the importance of the wear resistance properties in the performance and durability of prototypes in total hip joint replacement application, the unlubricated sliding wear experiments with commercial cubic zirconia, and stainless steel counterbody reveal that a combination of steady state COF of 0.5 and 0.42 and wear rate of 10-9 mm3/N m observed for the optimized ZTA composite with having the best combination of mechanical properties. The wear mechanism is dominated by abrasive wear and cracking induced delamination of tribolayer. In commensurate with the computer aided-design (CAD) of prototypes after optimization of process and properties of ZTA, the custom made modular steel-die mould assembly was fabricated to produce high strength green powder compact of Al2O3-5 wt% ZrO2 (3 mol %Y2O3)-800 ppm MgO without any geometric distortion at uniaxial pressure of 18 - 22 ton. In line with design consideration, green compact of the femoral head / acetabular socket was presintered at 1200oC in air for 2h in a conventional sintering furnace and subsequently computer numerical control (CNC) machined to a limited extent. The final stage of prototype development involved the multi-step sintering of the compact at 1600oC for 6h in air, followed by polishing using tailor made arrangement. The process quality was closely monitored by measuring dimensional changes at each manufacturing stage as well as the circularity measurement of final polished prototype. The microstructure as well as the physical properties in terms of hardness, indentation toughness, and burst strength is also reported. Taken together the present manufacturing approach appears to be a scalable and commercially viable fabrication strategy to make bioceramics based femoral head and acetabular socket biomedical devices

The computer-aided optimal heating schedule of forging ingots using the finite element method

This thesis presents the computer simulated thermal stress analysis of forging ingots during the heating and soaking periods. These results are then used to obtain the optimal heating schedule of these ingots. -- The equations for the transient nonlinear temperature distribution within the ingot due to the convective and radiative heat flux are derived using the nonlinear finite element analysis. The nonlinearities due to the variation of material properties have been taken into account by calculating the temperature at different time steps first and then at each time step the elemental property matrices are recalculated. The nonlinear algebraic equations are solved using three techniques and then the best technique is selected from these three for further analysis. -- The mathematical model for the thermal stress analysis has also been formulated using the finite element analysis. The temperatures obtained from the heat transfer analysis are used to calculate the force vector for the stress analysis. These finite element models are then used to calculate the effects of axial heat flux, the slenderness ratio of the ingot, and the linearization of the heat flux on the transient temperature and stress distributions within the ingot. -- The optimal heating schedule has been obtained considering two types of constraints; the first type of the constraint is that the stresses developed should not exceed certain value established by some of the commonly known failure theories, and the second type is that the temperature in the ingot during the heating or soaking period does not exceed a specified value for a particular type of material. The method of optimization of the furnace heating schedule is selected after considering three alternate ways of carrying out the optimization

Kurtosis-Based Feature Selection Method using Symmetric Uncertainty to Predict the Air Quality Index

Feature selection is vital in data pre-processing in machine learning, and it is prominent in datasets with many features. Feature selection analyses the relevant, irrelevant, and redundant features in the dataset. Feature selection removes the irrelevant features, which improves both the accuracy and prediction performance. The significant advantages of reducing the number of features from the dataset are reducing the training time, reducing overfitting, decreasing the curse of dimensionality, and simplifying the prediction model. The filter feature selection techniques can handle the issues with the high number of features, and this paper uses the symmetric uncertainty coefficient to verify the relevance of the independent features. In this paper, a new feature selection method named as kurtosis-based feature selection has been proposed to select the relevant features which affect the air pollution. Kurtosis-based feature selection is compared with seven filter feature selection techniques on air pollution dataset and validated the performance of the proposed algorithm. It has been observed that the kurtosis-based feature selection extracts only PM2.5 as the key feature and has been compared to the accuracy of the five existing methods. The experimental results illustrate that the kurtosis-based feature selection algorithm reduces the original feature set up to 91.66\%, but the existing filter feature selection techniques reduce the feature set to only 50\%

Outage Management System with Fault Passage Indicator

As the size and complexity of distribution networks is increasing, remote operated switches are being used to make the grid smarter. The distribution network is being continuously reconfigured to improve the voltage profile, reduce losses and to supply to a large number of customers. Consequently, when an outage occurs on this dynamically changing grid, it is difficult and time consuming to pin-point the location of the outage. In order to overcome this problem, fault passage indicators (FPIs) are installed at strategic locations on feeders at the branching points. FPI is a device which provides a remote and local visual indication of the occurrence of fault even after the isolation of line. While the technology of FPI is established, in this thesis, algorithms which are not sensitive to network reconfigurations, are presented for fast identification of fault location, based on the statuses of multiple FPIs received at the utility control center. Also a load flow simulation platform with fault passage indicators is presented, which suggests the state of the network and overall set of operations to be carried out by the outage management system, for a given network topology and data of the network provided by real time monitoring systems

Understanding and Forecasting of Credit Defaulters Using R- Programming

In Technology has provided numerous significant benefits to the financial industry. Financial transactions are now much smoother and faster than they were previously. Creditworthiness is a measure of how likely you are to repay your debt obligations, and it supports lenders decide whether or not to extend new credit to you. The current paper attempts to comprehend credit defaulters and develops a model to aid in understanding the determinants and prediction. A dataset of 376 responses was divided into training and testing data sets in proportions of 70% and 30%, respectively. The authors used traditional Binary Logistic Regression, Deep Learning, and Random Forest to achieve the empirical results. Logistic regression, an extension of linear regression with a categorical dependent variable, will also be used for comparison. IBM SPSS was used to run the binary logistic regression. and creates a model to aid in understanding the determinants and prediction

The SIRT1 Deacetylase Suppresses Intestinal Tumorigenesis and Colon Cancer Growth

Numerous longevity genes have been discovered in model organisms and altering their function results in prolonged lifespan. In mammals, some have speculated that any health benefits derived from manipulating these same pathways might be offset by increased cancer risk on account of their propensity to boost cell survival. The Sir2/SIRT1 family of NAD+-dependent deacetylases is proposed to underlie the health benefits of calorie restriction (CR), a diet that broadly suppresses cancer in mammals. Here we show that CR induces a two-fold increase SIRT1 expression in the intestine of rodents and that ectopic induction of SIRT1 in a β-catenin-driven mouse model of colon cancer significantly reduces tumor formation, proliferation, and animal morbidity in the absence of CR. We show that SIRT1 deacetylates β-catenin and suppresses its ability to activate transcription and drive cell proliferation. Moreover, SIRT1 promotes cytoplasmic localization of the otherwise nuclear-localized oncogenic form of β-catenin. Consistent with this, a significant inverse correlation was found between the presence of nuclear SIRT1 and the oncogenic form of β−catenin in 81 human colon tumor specimens analyzed. Taken together, these observations show that SIRT1 suppresses intestinal tumor formation in vivo and raise the prospect that therapies targeting SIRT1 may be of clinical use in β−catenin-driven malignancies

Canagliflozin and Cardiovascular and Renal Outcomes in Type 2 Diabetes Mellitus and Chronic Kidney Disease in Primary and Secondary Cardiovascular Prevention Groups

Background: Canagliflozin reduces the risk of kidney failure in patients with type 2 diabetes mellitus and chronic kidney disease, but effects on specific cardiovascular outcomes are uncertain, as are effects in people without previous cardiovascular disease (primary prevention). Methods: In CREDENCE (Canagliflozin and Renal Events in Diabetes With Established Nephropathy Clinical Evaluation), 4401 participants with type 2 diabetes mellitus and chronic kidney disease were randomly assigned to canagliflozin or placebo on a background of optimized standard of care. Results: Primary prevention participants (n=2181, 49.6%) were younger (61 versus 65 years), were more often female (37% versus 31%), and had shorter duration of diabetes mellitus (15 years versus 16 years) compared with secondary prevention participants (n=2220, 50.4%). Canagliflozin reduced the risk of major cardiovascular events overall (hazard ratio [HR], 0.80 [95% CI, 0.67-0.95]; P=0.01), with consistent reductions in both the primary (HR, 0.68 [95% CI, 0.49-0.94]) and secondary (HR, 0.85 [95% CI, 0.69-1.06]) prevention groups (P for interaction=0.25). Effects were also similar for the components of the composite including cardiovascular death (HR, 0.78 [95% CI, 0.61-1.00]), nonfatal myocardial infarction (HR, 0.81 [95% CI, 0.59-1.10]), and nonfatal stroke (HR, 0.80 [95% CI, 0.56-1.15]). The risk of the primary composite renal outcome and the composite of cardiovascular death or hospitalization for heart failure were also consistently reduced in both the primary and secondary prevention groups (P for interaction >0.5 for each outcome). Conclusions: Canagliflozin significantly reduced major cardiovascular events and kidney failure in patients with type 2 diabetes mellitus and chronic kidney disease, including in participants who did not have previous cardiovascular disease

Canagliflozin and renal outcomes in type 2 diabetes and nephropathy

BACKGROUND Type 2 diabetes mellitus is the leading cause of kidney failure worldwide, but few effective long-term treatments are available. In cardiovascular trials of inhibitors of sodium–glucose cotransporter 2 (SGLT2), exploratory results have suggested that such drugs may improve renal outcomes in patients with type 2 diabetes. METHODS In this double-blind, randomized trial, we assigned patients with type 2 diabetes and albuminuric chronic kidney disease to receive canagliflozin, an oral SGLT2 inhibitor, at a dose of 100 mg daily or placebo. All the patients had an estimated glomerular filtration rate (GFR) of 30 to <90 ml per minute per 1.73 m2 of body-surface area and albuminuria (ratio of albumin [mg] to creatinine [g], >300 to 5000) and were treated with renin–angiotensin system blockade. The primary outcome was a composite of end-stage kidney disease (dialysis, transplantation, or a sustained estimated GFR of <15 ml per minute per 1.73 m2), a doubling of the serum creatinine level, or death from renal or cardiovascular causes. Prespecified secondary outcomes were tested hierarchically. RESULTS The trial was stopped early after a planned interim analysis on the recommendation of the data and safety monitoring committee. At that time, 4401 patients had undergone randomization, with a median follow-up of 2.62 years. The relative risk of the primary outcome was 30% lower in the canagliflozin group than in the placebo group, with event rates of 43.2 and 61.2 per 1000 patient-years, respectively (hazard ratio, 0.70; 95% confidence interval [CI], 0.59 to 0.82; P=0.00001). The relative risk of the renal-specific composite of end-stage kidney disease, a doubling of the creatinine level, or death from renal causes was lower by 34% (hazard ratio, 0.66; 95% CI, 0.53 to 0.81; P<0.001), and the relative risk of end-stage kidney disease was lower by 32% (hazard ratio, 0.68; 95% CI, 0.54 to 0.86; P=0.002). The canagliflozin group also had a lower risk of cardiovascular death, myocardial infarction, or stroke (hazard ratio, 0.80; 95% CI, 0.67 to 0.95; P=0.01) and hospitalization for heart failure (hazard ratio, 0.61; 95% CI, 0.47 to 0.80; P<0.001). There were no significant differences in rates of amputation or fracture. CONCLUSIONS In patients with type 2 diabetes and kidney disease, the risk of kidney failure and cardiovascular events was lower in the canagliflozin group than in the placebo group at a median follow-up of 2.62 years

Performance Analysis and Improvement of 5G based Mission Critical Motion Control Applications

The industrial needs in the production of goods and control of processes within the factory keep leapfrogging daily by the necessities to fulfil the needs of the ever-growing population. In recent times, the industries are looking towards Industry 4.0 to improve their overall productivity and scalability. One of the significant aspects that are required to meet the requirements of Industry 4.0 is communication networks among industrial applications. Nowadays, industries from the cross markets are looking to replace their existing wired networks with wireless networks, which indeed brings many use-cases and a lot of new business models into existence. To make all these options possible, wireless networks need to meet the stringent requirements of these industrial applications in the form of reliability, latency, and service availability. This thesis focuses on a systematic methodology to integrate wireless networks like 5G, Wi-Fi 6, etc., into real-life automation devices. It also describes a methodology to evaluate their communication and control performance by varying control parameters like topology, cycle time, and type of networks. It also devises some techniques and methods that can improve the overall performance, i.e., both control and communication performance of the control applications. The method used to implement this work is a case study. This work integrates and tests the industrial applications in a real-life scenario. It is the best effort to bring a unique perspective of communication engineers and control engineers together regarding the performance of the industrial applications. This work tries to verify the suitability of the wireless in mission-critical control application scenarios with respect to their communication and control performance. Software for data analysis and visualization and its methodology for analyzing the traffic flow of the control applications via different wireless networks is demonstrated by varying different control parameters. It is shown that it is challenging for 5G to support the shorter cycle time values, and performance will get better and more stable with the increase in the cycle time of the control application. It is also found that the 1-Hop wireless topologies have a comparatively better control performance than 2-Hop wireless topologies. In the end, it is found that the communication and control performance of the motion control application can be improved by using the hybrid topology, which is a mixture of 5G and Wi-Fi 6, by modifying some key aspects. The thesis work helps to introduce a novel systematic methodology for measuring and analyzing the communication and control applications via different wireless networks. It also gives a better idea for the control engineers in the industry about which cycle times the different wireless networks and their topologies support when integrated with industrial automation devices. It also describes which wireless networks support industrial applications better. It ends with a novel methodology that could improve the performance of the mission-critical motion applications by using existing wireless technologies.